With the rapid development of the wireless communication technique, as the most precious resource in the wireless communication, the spectrum is increasingly demanded. Currently, the spectrum resource is usually allocated by the state to various organizations requiring the spectrum. Studies have shown that in the allocated spectrum resource, the utilization ratios of most frequency bands are lower than 25%, and some even lower than 10%. But the spectrum demand of some emerging wireless services and wireless devices cannot be satisfied. Thus how to effectively utilize the spectrum resource has become a hot issue in the field of wireless communication. The Cognitive Radio (CR) technique developed based on software radio technique emerges at the right moment. The CR technique sufficiently considers the low utilization ratio of the existing spectrum resource and the intellectualization evolution route of wireless communication technique, adaptively changes the application parameters according to the specific learning and decision-making algorithms by perceiving the ambient environment, and dynamically detects and selects idle spectrums that can be effectively utilized. The Dynamic Spectrum Access (DSA) is an important direction in the technical field of CR, and it allows multiple systems to share one band, and permits the lately accessed system to occupy the frequency without influencing other systems' communication. The precondition of the DSA technique is spectrum sensing, i.e., searching an available idle band, and the spectrum sensing is the prerequisite for the Secondary User (SU) to access the service. Since the sensing time demanded is short and the spectrum to be sensed has a large bandwidth, the current spectrum sensing technique has much difficulty.
The problem of the spectrum sensing technique can be solved using the spectrum measuring technique and the method for spectrum prediction. The spectrum measuring technique is one of the basic techniques for leading the cognitive radio technique to the actual applications.
The current spectrum measuring technique usually adopts the first order Markov process to predict the channel state, and the basic idea is to assume that the channel state in the current timeslot is only related to that of the previous timeslot; and the channel state transition occurs at the first moment of each timeslot.
During the implementation of the present invention, the inventors find that the prior art at least has the following problem.
In the spectrum prediction scheme of the first order Markov model, the channel state at the next moment is only related to the current channel state, and is not related much to the states in the historic timeslots of each channel. The correlativity between the channels is not specifically considered during the analysis process, and in case of multiple channels, the channels are generally assumed as being independent from each other. Thus, during the spectrum prediction process, the prediction accuracy for the spectrum state in the future timeslot is low, the miss ratio and omission ratio are high, and the spectrum hole selection is not reliable.